The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Scientific endeavors generally require precise and accurate quantification to determine results. In medicine and in the field of cardiology in particular, the results obtained from various tests are used in further decision-making regarding the patient including accurate diagnosis and treatment. Many tests, especially those involving imaging, provide results that require great skill to analyze by a trained expert or specialist. Due to the huge amount of information presented in an image and the lack of accurate fully automated systems for analysis, the field of medicine is frequently left to semi-quantitation (e.g., grade on a 1 to 4 scale). While this may be adequate for many purposes, observer bias, lack of reproducibility, and lack of the ability to be precise often results in the need for more testing to try to be certain of the diagnosis, or painstaking effort by the physician to make sure the treatment is given in the effective regions (e.g., that the proper location on the field of image is treated by X-rays, etc.). The ability to perform rapid and accurate quantification using computer-assisted image analysis can be a great aid in these fields.
Currently there have been great limitations in the full automation of image analysis. There are edge-detection system and methods available that look for a general change in the picture but generally require noise subtraction and input from a user to focus on the areas of interest or from an encyclopedic database to compare the image to in order to identify or delimit the object of interest in the image. The edges detected are generally based on first and second differentiation and are binary (edge present/absent) but not qualitative (do not reflect information about different types of edges present). Users of current processes need frequent and direct operator input to effectuate an analysis.
None of the current technologies and prior art, taken alone or in combination, address nor provide a utility solution for a fully automated precise image analysis and image quality assessment based on the extraction of predefined data from the input of images using a real-time simultaneous technology. The present invention can identify fine edges and distinguish between different objects without the need to make assumptions about the input image or to use filters or noise reduction methods that result in a net loss of data.
Specific uses and applications of this process include the field of coronary angiography and echocardiography. The raw images obtained in these arts including cineangiograms of the coronary arteries and echo images of the cardiac chamber walls until presently have not readily been amenable to accurate fully automated analysis of artery caliber (diameter along its length to evaluate amount of stenosis) or chamber dimensions and wall thickness.
In coronary angiography until present the cardiologist has had to estimate the percent stenosis along the length of the artery as revealed by the gold standard coronary angiogram (luminogram) or by other techniques including intravascular ultrasound or Computerized Tomographic (CT) scan. However, actual automation of this analysis is burdensome and currently has been inaccurate and therefore unreliable. Using the new detection methods inside a larger method of straightening the artery so that perpendicular cuts are obtained for measurement is providing the ability for both a fully automated and a more accurate analysis of the whole length of the artery.
In echocardiography field, there is currently no fully automated method of measuring cardiac chamber borders and dimensions. The input of the technologist is required in multiple steps of the image analysis. The new method is being developed to enable fully automated chamber measurements and wall thickness analyses and ejection fraction calculation. This would enable accurate noninvasive hemodynamic and cardiac output determinations.
Furthermore, great promise is expected in the field of artificial vision. By comparing two pictures temporally or side-by-side, with the fine resolution and discriminating abilities of the new method, the distances and dimensions of objects will be quickly amenable to calculation. By efficiently and automatically determining the shape and size of the object, automated identification should be greatly improved.
Further uses include the field of CT and MRI (magnetic resonance imaging) and ultrasound scans. The ability to accurately automatically measure chamber edges is expected to allow for automated analysis of normal and abnormal and for generation and comparison to encyclopedic database for further refinement of the art and science besides improving diagnosis and treatment for each individual patient. Another use would be for automated identification and marking of an organ edge for radiation therapy, for example.
US 20130278776 discloses a method for automatic left ventricular (LV) inner border detection. The method comprises the steps of: performing image mapping on an echocardiogram in order to produce a multi-level image map; converting the image map into a binary image by attributing pixels of one or more darker levels of the image map to the LV cavity and pixels of one or more lighter levels of the image map to the myocardium; applying a radial filter to contours of the myocardium in the binary image, to extract an approximate inner border of the LV; and performing shape modeling on the approximate inner border, to determine the LV inner border.
It should be emphasized that precision of shape modelling of edge lines in binary images strongly depends on a dynamic range of the original image. The narrow dynamic range results in lower precision of obtained edge line. Thus, there is a long-felt and unmet need to provide a method and a device that overcomes the problems associated with the prior art.